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Water Monitoring Trailing Mean Series
x402
Water Monitoring Trailing Mean Series is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-18).
Computes a trailing (rolling) mean series over water monitoring records (litres or cost) grouped by site and date, up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Water monitoring - Trailing mean series: Trailing mean series for Water monitoring. Up to 200 supplied typed records. Local numeric and data-quality processing; no external enrichment or forecasting. One of 25 profiles or calculations across 20 shared operations in this sector. 0.01 USDC includes one bounded trailing mean series deliverable.
Output
A series of trailing mean values computed over the specified numeric field (litres or cost), keyed per row, reflecting the rolling average over the chosen window size. Output is bounded to the supplied rows (up to 200) with no external enrichment or forecasting — purely local numeric processing.
Example use cases
Smoothing daily site water consumption
“I have daily water usage readings in litres for three sites over the past 30 days — can you calculate a 7-day trailing mean series so I can see the smoothed consumption trend per site?”
Rolling average cost analysis for utilities
“Here are 60 rows of water cost records by site and date. Compute a trailing mean series on the cost field with a window of 5 so I can spot spend trends without one-off spikes distorting the picture.”
Detecting anomalies in water usage data
“I want to compare raw daily litres to a 10-day rolling average for our monitoring sites — can you run a trailing mean series on these 120 water monitoring records using the litres field and a window of 10?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-sector-analytics-water-monitoring-rolling?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a fast, inexpensive ($0.01 USDC) local rolling mean computation on typed water monitoring records without needing external data enrichment or forecasting. It is ideal for smoothing daily site-level water usage or cost data, detecting trends, or preparing data for downstream analysis — particularly when working with up to 200 timestamped records across multiple sites.
Side effects
- Fewer rows supplied than the window size, producing no complete trailing windows
- Invalid date format (not YYYY-MM-DD) causing schema validation failure
- Null values in the selected field reducing effective window completeness
- Exceeding 200 row limit returns a validation error
- Invalid field enum value (must be 'litres' or 'cost') causes rejection
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| window | integer |
Tags
x402
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